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At least 937 records · Page 52

A Storm Surge and Inundation Model of the Back River Watershed at NASA Langley Research Center

This report on a Virginia Institute for Marine Science project demonstrates that the sub-grid modeling technology (now as part of Chesapeake Bay Inundation Prediction System, CIPS) can incorporate high-resolution Lidar measurements provided by NASA Langley Research Center into the sub-grid model framework to resolve detailed topographic features for use as a hydrological transport model for run-off simulations within NASA Langley and Langley Air Force Base. The rainfall over land accumulates in the ditches/channels resolved via the model sub-grid was tested to simulate the run-off induced by heavy precipitation. Possessing both the capabilities for storm surge and run-off simulations, the CIPS model was then applied to simulate real storm events starting with Hurricane Isabel in 2003. It will be shown that the model can generate highly accurate on-land inundation maps as demonstrated by excellent comparison of the Langley tidal gauge time series data (CAPABLE.larc.nasa.gov) and spatial patterns of real storm wrack line measurements with the model results simulated during Hurricanes Isabel (2003), Irene (2011), and a 2009 Nor'easter. With confidence built upon the model's performance, sea level rise scenarios from the ICCP (International Climate Change Partnership) were also included in the model scenario runs to simulate future inundation cases.

Loftis, Jon Derek↗

Supersonic Retropropulsion Test 1853 in NASA LaRC Unitary Plan Wind Tunnel Test Section 2

A supersonic retropropulsion experiment was conducted in the Langley Research Center Unitary Plan Wind Tunnel Test Section 2 at Mach numbers of 2.4, 3.5, and 4.6. Intended as a code validation effort, this study used pretest computations to size and refine the model such that tunnel blockage and internal flow separations were minimized. A 5-in diameter 70 degree sphere-cone forebody, which can accommodate up to four 4:1 area ratio nozzles, followed by a 9.55 inches long cylindrical aft body was selected for this test after computational maturation. The primary measurements for this experiment were high spatial-density surface pressures. In addition, high speed schlieren video and internal pressures and temperatures were acquired. The test included parametric variations in the number of nozzles utilized, thrust coefficients (roughly 0 to 4), and angles of attack (-8 to 20 degrees). The run matrix was developed to also allow quantification of various sources of experimental uncertainty, such as random errors due to run-to-run variations and systematic errors due to flowfield or model misalignments. To accommodate the uncertainty assessment, many runs and replicates were conducted with the model at various locations within the tunnel and with model roll angles of 0, 60, 120, and 180 degrees. This test report provides operational details of the experiment, contains a review of trends, and provides all schlieren and pressure results within appendices.

Berry, Scott A.↗

Development and Implementation of Dynamic Scripts to Support Local Model Verification at National Weather Service Weather Forecast Offices

Local modeling with a customized configuration is conducted at National Weather Service (NWS) Weather Forecast Offices (WFOs) to produce high-resolution numerical forecasts that can better simulate local weather phenomena and complement larger scale global and regional models. The advent of the Environmental Modeling System (EMS), which provides a pre-compiled version of the Weather Research and Forecasting (WRF) model and wrapper Perl scripts, has enabled forecasters to easily configure and execute the WRF model on local workstations. NWS WFOs often use EMS output to help in forecasting highly localized, mesoscale features such as convective initiation, the timing and inland extent of lake effect snow bands, lake and sea breezes, and topographically-modified winds. However, quantitatively evaluating model performance to determine errors and biases still proves to be one of the challenges in running a local model. Developed at the National Center for Atmospheric Research (NCAR), the Model Evaluation Tools (MET) verification software makes performing these types of quantitative analyses easier, but operational forecasters do not generally have time to familiarize themselves with navigating the sometimes complex configurations associated with the MET tools. To assist forecasters in running a subset of MET programs and capabilities, the Short-term Prediction Research and Transition (SPoRT) Center has developed and transitioned a set of dynamic, easily configurable Perl scripts to collaborating NWS WFOs. The objective of these scripts is to provide SPoRT collaborating partners in the NWS with the ability to evaluate the skill of their local EMS model runs in near real time with little prior knowledge of the MET package. The ultimate goal is to make these verification scripts available to the broader NWS community in a future version of the EMS software. This paper provides an overview of the SPoRT MET scripts, instructions for how the scripts are run, and example use cases.

Zavordsky, Bradley↗

Development and Implementation of Dynamic Scripts to Support Local Model Verification at National Weather Service Weather Forecast Offices

Local modeling with a customized configuration is conducted at National Weather Service (NWS) Weather Forecast Offices (WFOs) to produce high-resolution numerical forecasts that can better simulate local weather phenomena and complement larger scale global and regional models. The advent of the Environmental Modeling System (EMS), which provides a pre-compiled version of the Weather Research and Forecasting (WRF) model and wrapper Perl scripts, has enabled forecasters to easily configure and execute the WRF model on local workstations. NWS WFOs often use EMS output to help in forecasting highly localized, mesoscale features such as convective initiation, the timing and inland extent of lake effect snow bands, lake and sea breezes, and topographically-modified winds. However, quantitatively evaluating model performance to determine errors and biases still proves to be one of the challenges in running a local model. Developed at the National Center for Atmospheric Research (NCAR), the Model Evaluation Tools (MET) verification software makes performing these types of quantitative analyses easier, but operational forecasters do not generally have time to familiarize themselves with navigating the sometimes complex configurations associated with the MET tools. To assist forecasters in running a subset of MET programs and capabilities, the Short-term Prediction Research and Transition (SPoRT) Center has developed and transitioned a set of dynamic, easily configurable Perl scripts to collaborating NWS WFOs. The objective of these scripts is to provide SPoRT collaborating partners in the NWS with the ability to evaluate the skill of their local EMS model runs in near real time with little prior knowledge of the MET package. The ultimate goal is to make these verification scripts available to the broader NWS community in a future version of the EMS software. This paper provides an overview of the SPoRT MET scripts, instructions for how the scripts are run, and example use cases.

Zavodsky, Bradley↗

NASA SPoRT Modeling and Data Assimilation Research and Transition Activities Using WRF, LIS and GSI

weather research and forecasting ===== The NASA Short‐term Prediction Research and Transition (SPoRT) program has numerous modeling and data assimilation (DA) activities in which the WRF model is a key component. SPoRT generates realtime, research satellite products from the MODIS and VIIRS instruments, making the data available to NOAA/NWS partners running the WRF/EMS, including: (1) 2‐km northwestern‐hemispheric SST composite, (2) daily, MODIS green vegetation fraction (GVF) over CONUS, and (3) NASA Land Information System (LIS) runs of the Noah LSM over the southeastern CONUS. Each of these datasets have been utilized by specific SPoRT partners in local EMS model runs, with select offices evaluating the impacts using a set of automated scripts developed by SPoRT that manage data acquisition and run the NCAR Model Evaluation Tools verification package. SPoRT is engaged in DA research with the Gridpoint Statistical Interpolation (GSI) and Ensemble Kalman Filter in LIS for soil moisture DA. Ongoing DA projects using GSI include comparing the impacts of assimilating Atmospheric Infrared Sounder (AIRS) radiances versus retrieved profiles, and an analysis of extra‐tropical cyclones with intense non‐convective winds. As part of its Early Adopter activities for the NASA Soil Moisture Active Passive (SMAP) mission, SPoRT is conducting bias correction and soil moisture DA within LIS to improve simulations using the NASA Unified‐WRF (NU‐WRF) for both the European Space Agency's Soil Moisture Ocean Salinity and upcoming SMAP mission data. SPoRT has also incorporated real‐time global GVF data into LIS and WRF from the VIIRS product being developed by NOAA/NESDIS. This poster will highlight the research and transition activities SPoRT conducts using WRF, NU‐WRF, EMS, LIS, and GSI.

Case, Jonathan L.↗

The Vacuum-Compacted Regolith Gripping Mechanism and Unmanned Flights via Quad-Rotors

During the course of the Kennedy Space Center Summer Internship, two main experiments were performed: The Vacuum-Compacted Regolith Gripping Mechanism and Unmanned Flights via Quad-copters. The objectives of the Vacuum-Compacted Regolith Gripping Mechanism, often abbreviated as the Granular Gripper, are to exhibit Space Technology, such as a soft robotic hand, lift different apparatuses used to excavate regolith, and conserve energy while executing its intended task. The project is being conducted to test how much weight the Granular Gripper can hold. With the use of an Animatronic Robotic Hand, Arduino Uno, and other components, the system was calibrated before actually conducting the intended weight test. The maximum weight each finger could hold with the servos running, in the order of pinky, ring, middle, and index fingers, are as follows: 1.340N, 1.456 N, 0.9579 N, and 1.358 N. Using the small vacuum pump system, the maximum weight each finger could hold, in the same order, was: 4.076 N, 6.159 N, 5.454 N, and 4.052 N. The maximum torques on each of the fingers when the servos were running, in the same respective order, was: 0.0777 Nm, 0.0533 Nm, 0.0648 Nm, and 0.0532 Nm. The maximum torques on the individual fingers, when the small vacuum pump was in effect, in the same order as above, was: 0.2318 Nm, 0.3032 Nm, 0.2741 Nm, and 0.1618 Nm. In testing all the fingers with the servos running, the total weight was 5.112 N and the maximum torque on the all the fingers was 0.2515 Nm. However, when the small vacuum pump system was used, the total weight was 19.741 N and the maximum torque on the all the fingers was 0.9713 Nm. The conclusion that was drawn stated that using the small vacuum pump system proved nearly 4 times more effective when testing how much weigh the hand could hold. The resistance provided by the compacted sand in the glove allowed more weight to be held by the hand and glove. Also, when the servos turned off and the hand still retaining its position, energy is being saved because the vacuum created the same resistance the running servos did without using power. The Unmanned Flights via Quad-rotors are built because multi-rotor dynamics are an important starting point and fair analog for space craft control systems and they make good terrestrial development platforms for various aspects of control for space crafts. The project is being conducted to see what the thrust response is going to be when a pulse width modulation command is sent to the control system since the quad-rotors are PWM controlled. A simulation environment in constructed so that one can quickly iterate and test different designs such as control systems, PID control vs. LDR control, and state estimation. Using two DIY Quad Kits, APM 2.6, testing apparatus (called a data acquisition system) to test the quad-rotors, and a simulation program such as Simulink, two quad-rotors are built and controlled via a simulation program, which is designed to be as realistic as possible and not idealistic. Due to the quad-rotors not being completely built nor ready for testing, there are no results or conclusions to report.

Granular Gripper↗

Development and Testing of Functionally Operative and Visually Appealing Remote Firing Room Displays and Applications

This internship provided an opportunity for an intern to work with NASA's Ground Support Equipment (GSE) for the Spaceport Command and Control System (SCCS) at Kennedy Space Center as a remote display developer, under NASA technical mentor Kurt Leucht. The main focus was on creating remote displays and applications for the hypergolic and high pressure helium subsystem team to help control the filling of the respective tanks. As a remote display and application developer for the GSE hypergolic and high pressure helium subsystem team the intern was responsible for creating and testing graphical remote displays and applications to be used in the Launch Control Center (LCC) on the Firing Room's computers. To become more familiar with the subsystem, the individual attended multiple project meetings and acquired their specific requirements regarding what needed to be included in the software. After receiving the requirements for the displays, the next step was to create displays that had both visual appeal and logical order using the Display Editor, on the Virtual Machine (VM). In doing so, all Compact Unique Identifiers (CUI), which are associated with specific components within the subsystem, were need to be included in each respective display for the system to run properly. Then, once the display was created it was to be tested to ensure that the display runs as intended by using the Test Driver, also found on the VM. This Test Driver is a specific application that checks to make sure all the CUIs in the display are running properly and returning the correct form of information. After creating and locally testing the display it needed to go through further testing and evaluation before deemed suitable for actual use. For the remote applications the intern was responsible for creating a project that focused on channelizing each component included in each display. The core of the application code was created by setting up spreadsheets and having an auto test generator, generate the complete code structure. This application code was then loaded and ran on a testing environment set to ensure the code runs as anticipated. By the end of the semester-long experience at NASA's Kennedy Space Center, the individual should have gained great knowledge and experience in various areas of both display and application development and testing. They were able to demonstrate this new knowledge obtained by creating multiple successful remote displays that will one day be used by the hypergolic and high pressure helium subsystem team in the LCC's firing rooms to service the new Orion spacecraft. The completed display channelization application will be used to receive verification from NASA quality engineers.

Display Devices↗

High-Resolution Mesoscale Model Setup for the Eastern Range and Wallops Flight Facility

Mesoscale weather conditions can have an adverse effect on space launch, landing, ground processing, and weather advisories, watches, and warnings at the Eastern Range (ER) in Florida and Wallops Flight Facility (WFF) in Virginia. During summer, land-sea interactions across Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) lead to sea breeze front formation, which can spawn deep convection that can hinder operations and endanger personnel and resources. Many other weak locally-driven low-level boundaries and their interactions with the sea breeze front and each other can also initiate deep convection in the KSC/CCAFS area. These convective processes often last 60 minutes or less and pose a significant challenge to the local forecasters. Surface winds during the transition seasons (spring and fall) pose the most difficulties for the forecasters at WFF. They also encounter problems forecasting convective activity and temperature during those seasons. Therefore, accurate mesoscale model forecasts are needed to better forecast a variety of unique weather phenomena. Global and national scale models cannot properly resolve important local-scale weather features at each location due to their horizontal resolutions being much too coarse. Therefore, a properly tuned local data assimilation (DA) and forecast model at a high resolution is needed to provide improved capability. To accomplish this, a number of sensitivity tests were performed using the Weather Research and Forecasting (WRF) model in order to determine the best DA/model configuration for operational use at each of the space launch ranges to best predict winds, precipitation, and temperature. A set of Perl scripts to run the Gridpoint Statistical Interpolation (GSI)/WRF in real-time were provided by NASA's Short-term Prediction Research and Transition Center (SPoRT). The GSI can analyze many types of observational data including satellite, radar, and conventional data. The GSI/WRF scripts use a cycled GSI system similar to the operational North American Mesoscale (NAM) model. The scripts run a 12-hour pre-cycle in which data are assimilated from 12 hours prior up to the model initialization time. A number of different model configurations were tested for both the ER and WFF by varying the horizontal resolution on which the data assimilation was done. Three different grid configurations were run for the ER and two configurations were run for WFF for archive cases from 27 Aug 2013 through 10 Nov 2013. To quantify model performance, standard model output will be compared to the Meteorological Assimilation Data Ingest System (MADIS) data. The MADIS observation data will be compared to the WRF forecasts using the Model Evaluation Tools (MET) verification package. In addition, the National Centers for Environmental Prediction's Stage IV precipitation data will be used to validate the WRF precipitation forecasts. The author will summarize the relative skill of the various WRF configurations and how each configuration behaves relative to the others, as well as determine the best model configuration for each space launch range.

Watson, Leela R.↗

Summer 2015 Internship Abstract

Green fluorescent protein (GFP) visually shows the expression of proteins by fluorescing when exposed to certain wavelengths of light. The GFP in this experiment was used to identify cells actively releasing viruses. The experiment focused on the effect of microgravity on the GFP expression of Akata B-cells infected with Epstein Barr Virus (EBV). Two flasks were prepared with 30 million cells each and two bioreactors were prepared with 50 million cells each. All four cultures were incubated for 16 days and fed every four days. Cellometer readings were taken on the feeding days to find cell size, viability, and GFP expression. In addition, the cells were treated with Propodium monoazide (PMA) and run through real time PCR to determine viral load on the feeding days. On the International Space Station air samples are taken to analyze the bacterial and fungal organisms in the air. The Sartorius Portable Airport is being investigated for potential use on the ISS to analyze for viral content in the air. Multiple samples were taken around Johnson Space Center building 37 and in Clear Lake Pediatric Clinic. The filter used was the gelatin membrane filter and the DNA was extracted directly from the filter. The DNA was then run through real time PCR for Varicella Zoster Virus (VZV) and EBV as well as GAPDH to test for the presence of DNA. The results so far have shown low DNA yield and no positive results for VZV or EBV. Further inquiry involves accurately replicating an atmosphere with high viral load from saliva as would be found on the ISS to run the air sampler in. Another line of research is stress hormones that may be correlated to the reactivation of latent viruses. The stress hormones from saliva samples are analyzed rather than blood samples. The quantity found in saliva shows the quantity of the hormones actually attached to cells and causing a reaction, whereas in the blood the quantity of hormones is the total amount released to cause a reaction. The particular hormones tested for were cortisol, alpha-amylase, and DHEA. The DHEA was very high in the two control samples tested. Regularly, samples came into the lab from local clinics to be tested for various viruses. Saliva, blood, body scrapes, and tears were received from the clinics and then run for VZV, EBV, and Human Simplex Virus 1 (HSV-1) with the results then reported back to the clinician. Blood, saliva, and urine from astronauts were also tested for viruses and logged. In addition, several cell cultures were brought up and grown, including adherent Human Lung Fibroblast (HFL) cells infected with VZV, and Akata B-cells infected with EBV.

Smith, Courtney↗

Telescience Resource Kit (TReK)

Telescience Resource Kit (TReK) is one of the Huntsville Operations Support Center (HOSC) remote operations solutions. It can be used to monitor and control International Space Station (ISS) payloads from anywhere in the world. It is comprised of a suite of software applications and libraries that provide generic data system capabilities and access to HOSC services. The TReK Software has been operational since 2000. A new cross-platform version of TReK is under development. The new software is being released in phases during the 2014-2016 timeframe. The TReK Release 3.x series of software is the original TReK software that has been operational since 2000. This software runs on Windows. It contains capabilities to support traditional telemetry and commanding using CCSDS (Consultative Committee for Space Data Systems) packets. The TReK Release 4.x series of software is the new cross platform software. It runs on Windows and Linux. The new TReK software will support communication using standard IP protocols and traditional telemetry and commanding. All the software listed above is compatible and can be installed and run together on Windows. The new TReK software contains a suite of software that can be used by payload developers on the ground and onboard (TReK Toolkit). TReK Toolkit is a suite of lightweight libraries and utility applications for use onboard and on the ground. TReK Desktop is the full suite of TReK software -most useful on the ground. When TReK Desktop is released, the TReK installation program will provide the option to choose just the TReK Toolkit portion of the software or the full TReK Desktop suite. The ISS program is providing the TReK Toolkit software as a generic flight software capability offered as a standard service to payloads. TReK Software Verification was conducted during the April/May 2015 timeframe. Payload teams using the TReK software onboard can reference the TReK software verification. TReK will be demonstrated on-orbit running on an ISS provided T61p laptop. Target Timeframe: September 2015 -2016. The on-orbit demonstration will collect benchmark metrics, and will be used in the future to provide live demonstrations during ISS Payload Conferences. Benchmark metrics and demonstrations will address the protocols described in SSP 52050-0047 Ku Forward section 3.3.7. (Associated term: CCSDS File Delivery Protocol (CFDP)).

Lippincott, Jeff↗

SLS Test Stand Site Selection

Test site selection is a critical element of the design, development and production of a new system. With the advent of the new Space Launch System (SLS), the National Aeronautics and Space Administration (NASA) had a number of test site selection decisions that needed to be made early enough in the Program to support the planned Launch Readiness Date (LRD). This case study focuses on decisions that needed to be made in 2011 and 2012 in preparation for the April 2013 DPMC decision about where to execute the Main Propulsion Test that is commonly referred to as "Green Run." Those decisions relied upon cooperative analysis between the Program, the Test Lab and Center Operations. The SLS is a human spaceflight vehicle designed to carry a crew farther into space than humans have previously flown. The vehicle consists of four parts: the crew capsule, the upper stage, the core stage, and the first stage solid rocket boosters. The crew capsule carries the astronauts, while the upper stage, the core stage, and solid rocket boosters provide thrust for the vehicle. In other words, the stages provide the "lift" part of the lift vehicle. In conjunction with the solid rocket boosters, the core stage provides the initial "get-off-the-ground" thrust to the vehicle. The ignition of the four core stage engines and two solid rocket boosters is the first step in the launch portion of the mission. The solid rocket boosters burn out after about 2 minutes of flight, and are then jettisoned. The core stage provides thrust until the vehicle reaches a specific altitude and speed, at which point the core stage is shut off and jettisoned, and the upper stage provides vehicle thrust for subsequent mission trajectories. The integrated core stage primarily consists of a liquid oxygen tank, a liquid hydrogen tank, and the four core stage engines. For the SLS program, four RS-25 engines were selected as the four core stage engines. The RS-25 engine is the same engine that was used for Space Shuttle. The test plan for the integrated core stage was broken down into several segments: Component testing, system level testing, and element level testing. In this context, components are items such as valves, controllers, sensors, etc. Systems are items such as an entire engine, a tank, or the outer stage body. The core stage itself is considered to be an element. The rocket engines are also considered an element. At the program level, it was decided to perform a single green run test on the integrated core stage prior to shipment of it to Kennedy Space Center (KSC) for use in the EM-1 test flight of the SLS vehicle. A green run test is the first live fire of the new integrated core stage and engine elements - without boosters of course. The SLS Program had to decide where to perform SLS green run testing.

Crowe, Kathryn↗

Using Natural Language to Enhance Mission Effectiveness

The availability of highly capable, yet relatively cheap, unmanned aerial vehicles (UAVs) is opening up new areas of use for hobbyists and for professional-related activities. The driving function of this research is allowing a non-UAV pilot, an operator, to define and manage a mission. This paper describes the preliminary usability measures of an interface that allows an operator to define the mission using speech to make inputs. An experiment was conducted to begin to enumerate the efficacy and user acceptance of using voice commands to define a multi-UAV mission and to provide high-level vehicle control commands such as "takeoff." The primary independent variable was input type - voice or mouse. The primary dependent variables consisted of the correctness of the mission parameter inputs and the time needed to make all inputs. Other dependent variables included NASA-TLX workload ratings and subjective ratings on a final questionnaire. The experiment required each subject to fill in an online form that contained comparable required information that would be needed for a package dispatcher to deliver packages. For each run, subjects typed in a simple numeric code for the package code. They then defined the initial starting position, the delivery location, and the return location using either pull-down menus or voice input. Voice input was accomplished using CMU Sphinx4-5prealpha for speech recognition. They then inputted the length of the package. These were the option fields. The subject had the system "Calculate Trajectory" and then "Takeoff" once the trajectory was calculated. Later, the subject used "Land" to finish the run. After the voice and mouse input blocked runs, subjects completed a NASA-TLX. At the conclusion of all runs, subjects completed a questionnaire asking them about their experience in inputting the mission parameters, and starting and stopping the mission using mouse and voice input. In general, the usability of voice commands is acceptable. With a relatively well-defined and simple vocabulary, the operator can input the vast majority of the mission parameters using simple, intuitive voice commands. However, voice input may be more applicable to initial mission specification rather than for critical commands such as the need to land immediately due to time and feedback constraints. It would also be convenient to retrieve relevant mission information using voice input. Therefore, further on-going research is looking at using intent from operator utterances to provide the relevant mission information to the operator. The information displayed will be inferred from the operator's utterances just before key phrases are spoken. Linguistic analysis of the context of verbal communication provides insight into the intended meaning of commonly heard phrases such as "What's it doing now?" Analyzing the semantic sphere surrounding these common phrases enables us to predict the operator's intent and supply the operator's desired information to the interface. This paper also describes preliminary investigations into the generation of the semantic space of UAV operation and the success at providing information to the interface based on the operator's utterances.

Trujillo, Anna C.↗

Computational Approaches to Simulation and Optimization of Global Aircraft Trajectories

This study examines three possible approaches to improving the speed in generating wind-optimal routes for air traffic at the national or global level. They are: (a) using the resources of a supercomputer, (b) running the computations on multiple commercially available computers and (c) implementing those same algorithms into NASAs Future ATM Concepts Evaluation Tool (FACET) and compares those to a standard implementation run on a single CPU. Wind-optimal aircraft trajectories are computed using global air traffic schedules. The run time and wait time on the supercomputer for trajectory optimization using various numbers of CPUs ranging from 80 to 10,240 units are compared with the total computational time for running the same computation on a single desktop computer and on multiple commercially available computers for potential computational enhancement through parallel processing on the computer clusters. This study also re-implements the trajectory optimization algorithm for further reduction of computational time through algorithm modifications and integrates that with FACET to facilitate the use of the new features which calculate time-optimal routes between worldwide airport pairs in a wind field for use with existing FACET applications. The implementations of trajectory optimization algorithms use MATLAB, Python, and Java programming languages. The performance evaluations are done by comparing their computational efficiencies and based on the potential application of optimized trajectories. The paper shows that in the absence of special privileges on a supercomputer, a cluster of commercially available computers provides a feasible approach for national and global air traffic system studies.

global air traffic optimization↗

On the Feasibility of Monitoring Carbon Monoxide in the Lower Troposphere from a Constellation of Northern Hemisphere Geostationary Satellites: Global Scale Assimilation Experiments (Part II)

This paper describes the second phase of an Observing System Simulation Experiment (OSSE) that utilizes the synthetic measurements from a constellation of satellites measuring atmospheric composition from geostationary (GEO) Earth orbit presented in part I of the study. Our OSSE is focused on carbon monoxide observations over North America, East Asia and Europe where most of the anthropogenic sources are located. Here we assess the impact of a potential GEO constellation on constraining northern hemisphere (NH) carbon monoxide (CO) using data assimilation. We show how cloud cover affects the GEO constellation data density with the largest cloud cover (i.e., lowest data density) occurring during Asian summer. We compare the modeled state of the atmosphere (Control Run), before CO data assimilation, with the known 'true' state of the atmosphere (Nature Run) and show that our setup provides realistic atmospheric CO fields and emission budgets. Overall, the Control Run underestimates CO concentrations in the northern hemisphere, especially in areas close to CO sources. Assimilation experiments show that constraining CO close to the main anthropogenic sources significantly reduces errors in NH CO compared to the Control Run. We assess the changes in error reduction when only single satellite instruments are available as compared to the full constellation. We find large differences in how measurements for each continental scale observation system affect the hemispherical improvement in long-range transport patterns, especially due to seasonal cloud cover. A GEO constellation will provide the most efficient constraint on NH CO during winter when CO lifetime is longer and increments from data assimilation associated with source regions are advected further around the globe.

Geo Stationary Constellation↗

Abstract - Belbas, Nicholas (EC2)

Originally, I was brought into the Design and Analysis Branch in the Crew and Thermal Systems to work on administrative tasks like archiving and scheduling. However, I ended up splitting my time between secretarial tasks and a technical project. My technical project was originally meant to be a wireless sensor package for the 20ft Spacecraft Thermal Vacuum Chamber in the B7 High Bay. I would be using a miniature wifi development board and a temperature/humidity sensor along with custom 3D modeling to accomplish this. However, after some discussion with my technical mentor, the plan was changed to a mobile autonomous self-charging sensor platform. A mobile platform will allow the sensors to be moved around without depressurizing the chamber. Also, the self-charging aspect of the package allows for almost unlimited time in the chamber. If the on-board battery runs low, the robot can easily be driven to its charging dock and continue to transmit while charging. The driving base is based around a Raspberry Pi 3 board with a 12C PMW DC Motor controller and a PWM controller driving two small gear motors. The sensor transmitter itself is a RHT03 temperature and humidity sensor and Cozir CO2 sensor connected to an ESP8266 Huzzah board. The power distribution system utilizes a pair of 3.7v 3600mah lipo batteries wired to Powerboost 500 boards. Also, the self-charging mechanism utilizes two 12v-max inductive charging coils wired into the same Powerboost boards as the battery. The Raspberry pi is running Python 3.3 for the driving base and Javascript MJPEG library for transmitting live video from the onboard camera. The sensor package is running Arduino-based C++ and the program capturing the data is running PyqtGraph Python and HTML. The shell of the robot itself is a 3D printed case that will (work in progress) snap together. The photo to the left shows the two halves separated from each other. The black shell contains the power distribution boards and connectors while the white shell contains the driving base and data systems.

Belbas, Nicholas↗

OpenSatKit Enables Quick Startup for CubeSat Missions

The software required to develop, integrate, and operate a spacecraft is substantial regardless of whether its a large or small satellite. Even getting started can be a monumental task. To solve this problem, NASAs Core Flight System (cFS), NASA's 42 spacecraft dynamics simulator, and Ball Aerospaces COSMOS ground system have been integrated together into a kit called OpenSatKit that provides a complete and open source software solution for starting a new satellite mission. Users can have a working system with flight software, dynamics simulation, and a ground command and control system up and running within hours.Every satellite mission requires three primary categories of software to function. The first is Flight Software (FSW) which provides the onboard control of the satellites and its payload(s). NASA's cFS provides a great platform for developing this software. Second, while developing a satellite on earth, it is necessary to simulate the satellites orbit, attitude, and actuators, to ensure that the systems that control these aspects will work correctly in the real environment. NASAs 42 simulator provides these functionalities. Finally, the ground has to be able to communicate with the satellite, monitor its performance and health, and display its data. Additionally, test scripts have to be written to verify the system on the ground. Ball Aerospace's COSMOS command and control system provides this functionality. Once the OpenSatKit is up and running, the next step is to customize the platform and get it running on the end target. Starting from a fully working system makes porting the cFS from Linux to a users platform much easier. An example Raspberry Pi target is included in the kit so users can gain experience working with a low cost hardware target. All users can benefit from OpenSatKit but the greatest impact and benefits will be to SmallSat missions with constrained budgets and small software teams. This paper describes OpenSatKits system design, the steps necessary to run the system to target the Raspberry Pi, and future plans. OpenSatKit is a free fully functional spacecraft software system that we hope will greatly benefit the SmallSat community.

Software↗

Gravity-Assist Trajectories to the Ice Giants: An Automated Method to Catalog Mass- Or Time-Optimal Solutions

This work presents an automated method of calculating mass (or time) optimal gravity-assist trajectories without a priori knowledge of the flyby-body combination. Since gravity assists are particularly crucial for reaching the outer Solar System, we use the Ice Giants, Uranus and Neptune, as example destinations for this work. Catalogs are also provided that list the most attractive trajectories found over launch dates ranging from 2024 to 2038. The tool developed to implement this method, called the Python EMTG Automated Trade Study Application (PEATSA), iteratively runs the Evolutionary Mission Trajectory Generator (EMTG), a NASA Goddard Space Flight Center in-house trajectory optimization tool. EMTG finds gravity-assist trajectories with impulsive maneuvers using a multiple-shooting structure along with stochastic methods (such as monotonic basin hopping) and may be run with or without an initial guess provided. PEATSA runs instances of EMTG in parallel over a grid of launch dates. After each set of runs completes, the best results within a neighborhood of launch dates are used to seed all other cases in that neighborhood-allowing the solutions across the range of launch dates to improve over each iteration. The results here are compared against trajectories found using a grid-search technique, and PEATSA is found to outperform the grid-search results for most launch years considered.

Hughes, Kyle M.↗

Gravity-Assist Trajectories to the Ice Giants: An Automated Method to Catalog Mass-or Time-Optimal Solutions

This work presents an automated method of calculating mass (or time) optimal gravity-assist trajectories without a priori knowledge of the flyby-body combination. Since gravity assists are particularly crucial for reaching the outer Solar System, we use the Ice Giants, Uranus and Neptune, as example destinations for this work. Catalogs are also provided that list the most attractive trajectories found over launch dates ranging from 2024 to 2038. The tool developed to implement this method, called the Python EMTG Automated Trade Study Application (PEATSA), iteratively runs the Evolutionary Mission Trajectory Generator (EMTG), a NASA Goddard Space Flight Center in-house trajectory optimization tool. EMTG finds gravity-assist trajectories with impulsive maneuvers using a multiple-shooting structure along with stochastic methods (such as monotonic basin hopping) and may be run with or without an initial guess provided. PEATSA runs instances of EMTG in parallel over a grid of launch dates. After each set of runs completes, the best results within a neighborhood of launch dates are used to seed all other cases in that neighborhood---allowing the solutions across the range of launch dates to improve over each iteration. The results here are compared against trajectories found using a grid-search technique, and PEATSA is found to outperform the grid-search results for most launch years considered.

Hughes, Kyle M.↗